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Phosphorylated H2AX (γ-H2AX) is a sensitive marker for DNA double-strand breaks (DSBs), but the variability of H2AX expression in different cell and tissue types makes it difficult to interpret the meaning of the γ-H2AX level. Furthermore, the assays commonly used for γ-H2AX detection utilize laborious and low-throughput microscopy-based methods. We describe here an ELISA assay that measures both phosphorylated H2AX and total H2AX absolute amounts to determine the percentage of γ-H2AX, providing a normalized value representative of the amount of DNA damage. We demonstrate the utility of the assay to measure DSBs introduced by either ionizing radiation or DNA-damaging agents in cultured cells and in xenograft models. Furthermore, utilizing the NCI-60 cancer cell line panel, we show a correlation between the basal fraction of γ-H2AX and cellular mutation levels. This additional application highlights the ability of the assay to measure γ-H2AX levels in many extracts at once, making it possible to correlate findings with other cellular characteristics. Overall, the γ-H2AX ELISA represents a novel approach to quantifying DNA damage, which may lead to a better understanding of mutagenic pathways in cancer and provide a useful biomarker for monitoring the effectiveness of DNA-damaging anticancer agents.

Exposure to oxygen-rich environments can lead to oxidative damage, increased body iron stores, and changes in status of some vitamins, including folate. Assessing the type of oxidative damage in these environments and determining its relationships with changes in folate status are important for defining nutrient requirements and designing countermeasures to mitigate these effects. Responses of humans to oxidative stressors were examined in participants undergoing a saturation dive in an environment with increased partial pressure of oxygen, a NASA Extreme Environment Mission Operations mission. Six participants completed a 13-d saturation dive in a habitat 19 m below the ocean surface near Key Largo, FL. Fasting blood samples were collected before, twice during, and twice after the dive and analyzed for biochemical markers of iron status, oxidative damage, and vitamin status. Body iron stores and ferritin increased during the dive (P

Topoisomerase I (Top1) is a proven target for cancer therapeutics. Recent data from the Fluorouracil, Oxaliplatin, CPT-11: Use and Sequencing (FOCUS) trial demonstrated that nuclear staining of Top1 correlates with chemotherapeutic efficacy. Such a correlation may help identify patients likely to respond to Top1 inhibitors and illuminate their mechanism of action. Cellular response to Top1 inhibitors is complex, but Top1 target engagement is a necessary first step in this process. This paper reports the development and validation of a quantitative immunoassay for Top1 in tumors.We have developed and validated a two-site enzyme chemiluminescent immunoassay for quantifying Top1 levels in tumor biopsies. Analytical validation of the assay established the inter-day coefficient of variation at 9.3%±3.4% and a 96.5%±7.3% assay accuracy. Preclinical fit-for-purpose modeling of topotecan time- and dose-effects was performed using topotecan-responsive and -nonresponsive xenografts in athymic nude mice. Higher baseline levels of Top1 were observed in topotecan-responsive than -nonresponsive tumors. Top1 levels reached a maximal decrease 4 to 7 hours following treatment of engrafted mice with topotecan and the indenoisoquinoline NSC 724998.Our analysis of Top1 levels in control and treated tumors supports the previously proposed mechanism of action for Top1 inhibitor efficacy, wherein higher baseline Top1 levels lead to formation of more covalent-complex-dependent double-strand break damage and, ultimately, cell death. In contrast, xenografts with lower baseline Top1 levels accumulate fewer double-stand breaks, and may be more resistant to Top1 inhibitors. Our results support further investigation into the use of Top1 levels in tumors as a potential predictive biomarker. The Top1 immunoassay described in this paper has been incorporated into a Phase I clinical trial at the National Cancer Institute to assess pharmacodynamic response in tumor biopsies and determine whether baseline Top1 levels are predictive of response to indenoisoquinoline Top1 inhibitors.

Poly(ADP-ribose) polymerase (PARP) facilitates DNA repair and PARP inhibitors may potentiate the effect of DNA-damaging chemotherapeutic agents in patients with cancer. Collection of peripheral blood mononuclear cells (PBMCs) as a surrogate tissue to monitor PARP inhibitor pharmacodynamic effects has several advantages over tumor biopsy collection, including minimally invasive sample collection and the ability to collect multiple samples for longitudinal assessment of drug effect.Using our previously validated immunoassay for measuring poly(ADP-ribose) (PAR), a product of PARP, in tumor biopsies, we validated a method to quantify PAR levels in PBMCs to monitor the pharmacodynamic effects of the PARP inhibitor ABT-888 in clinical trials. The inter-individual variation in PAR levels was large. No significant difference (P = 0.67) was measured between median baseline PAR levels in 144 healthy volunteers (131.7 pg/1×10(7) PBMCs [interquartile range, 79.5-241.6]) and 49 patients with cancer (149.2 pg/1×10(7) PBMCs [interquartile range, 83.2-249.3]). In addition, PAR levels monitored in healthy volunteers over 3 weeks had considerable intra- and inter-individual variation (range, 44-1073 pg PAR/1×10(7) PBMCs). As a pharmacodynamic model, we quantified changes in PAR levels in human PBMCs treated ex vivo with clinically relevant concentrations of ABT-888. Of 40 healthy volunteer PBMC samples treated with ABT-888, 47.5% had greater than 50% PAR reduction compared to vehicle-treated controls. Considerable inter-sample heterogeneity in PAR levels was measured, and several ABT-888-insensitive samples were identified.Our results emphasize the importance of using a validated method to measure PAR levels, and support further investigation into the role of PARP in PBMCs. To this end, the PAR immunoassay has been validated for use with PBMCs and incorporated into clinical trials to assess PBMCs as a potential pharmacodynamic surrogate for tumor biopsies in clinical trials of PARP inhibitors.

Wildfires are becoming more frequent due to the global climate change. Large amounts of greenhouse gases emitted by wildfires can lead to increases in extreme climate events. Accurately estimating the greenhouse gas carbon dioxide (CO2) emissions from wildfires is important for mitigation of climate change. In this paper, we develop a novel method to estimate wildfire CO2 emissions from the relationship between local CO2 emissions and XCO2 anomalies. Our method uses the WRF-Chem assimilation system from OCO-2 XCO2 retrievals which coupled with Data Assimilation Research Testbed (DART). To validate our results, we conducted three experiments evaluating the wildfire CO2 emissions over the conterminous United States. The four-month average wildfire emissions from July to October in 2015∼2018 were estimated at 4.408 Tg C, 1.784 Tg C, 1.514 Tg C and 2.873 Tg C, respectively. Compared to the average of established inventories CT2019B, FINNv1.5 and GFASv1.2 fire emissions, our estimates fall within one standard deviation, except for 2017 due to lacking of OCO-2 XCO2 retrievals. These results suggest that the regional carbon assimilation system, such as WRF-Chem/DART, using OCO-2 XCO2 retrievals has a great potential for accurately tracking regional wildfire emissions.

Quick and automatic detection of the distribution and connectivity of urban rivers and their changes from satellite imagery is of great importance for urban flood control, river management, and ecological conservation. By improving the E-UNet model, this study proposed a cascaded river segmentation and connectivity reconstruction deep learning network model (WaterSCNet) to segment urban rivers from Sentinel-2 multi-spectral imagery and simultaneously reconstruct their connectivity obscured by road and bridge crossings from the segmentation results. The experimental results indicated that the WaterSCNet model could achieve better river segmentation and connectivity reconstruction results compared to the E-UNet, U-Net, SegNet, and HRNet models. Compared with the classic U-Net model, the MCC, F1, Kappa, and Recall evaluation metrics of the river segmentation results of the WaterSCNet model were improved by 3.24%, 3.10%, 3.36%, and 3.93%, respectively, and the evaluation metrics of the connectivity reconstruction results were improved by 4.25%, 4.11%, 4.37%, and 4.83%, respectively. The variance of the evaluation metrics of the five independent experiments indicated that the WaterSCNet model also had the best robustness compared to the other four models.

In the published article [...]

High spatial resolution carbon dioxide (CO2) flux inversion systems are needed to support the global stocktake required by the Paris Agreement and to complement the bottom-up emission inventories. Based on the work of Zhang, a regional CO2 flux inversion system capable of assimilating the column-averaged dry air mole fractions of CO2 (XCO2) retrieved from Orbiting Carbon Observatory-2 (OCO-2) observations had been developed. To evaluate the system, under the constraints of the initial state and boundary conditions extracted from the CarbonTracker 2017 product (CT2017), the annual CO2 flux over the contiguous United States in 2016 was inverted (1.08 Pg C yr−1) and compared with the corresponding posterior CO2 fluxes extracted from OCO-2 model intercomparison project (OCO-2 MIP) (mean: 0.76 Pg C yr−1, standard deviation: 0.29 Pg C yr−1, 9 models in total) and CT2017 (1.19 Pg C yr−1). The uncertainty of the inverted CO2 flux was reduced by 14.71% compared to the prior flux. The annual mean XCO2 estimated by the inversion system was 403.67 ppm, which was 0.11 ppm smaller than the result (403.78 ppm) simulated by a parallel experiment without assimilating the OCO-2 retrievals and closer to the result of CT2017 (403.29 ppm). Independent CO2 flux and concentration measurements from towers, aircraft, and Total Carbon Column Observing Network (TCCON) were used to evaluate the results. Mean bias error (MBE) between the inverted CO2 flux and flux measurements was 0.73 g C m−2 d−1, was reduced by 22.34% and 28.43% compared to those of the prior flux and CT2017, respectively. MBEs between the CO2 concentrations estimated by the inversion system and concentration measurements from TCCON, towers, and aircraft were reduced by 52.78%, 96.45%, and 75%, respectively, compared to those of the parallel experiment. The experiment proved that CO2 emission hotspots indicated by the inverted annual CO2 flux with a relatively high spatial resolution of 50 km consisted well with the locations of most major metropolitan/urban areas in the contiguous United States, which demonstrated the potential of combing satellite observations with high spatial resolution CO2 flux inversion system in supporting the global stocktake.